Conventional search engines receive requests from users that are seeking information. The requests are formulated on computing devices used by the users. The computing devices may include input interfaces, e.g., touch screens, keyboards, keypads, etc., that receive the requests. Users may have difficulty entering the requests into the conventional input interfaces because of disabilities associated with the user, large fingers, or awkward configurations for the conventional input interfaces.
Some conventional computing devices are configured to provide query suggestions to the user based on the number of characters received from the input interface. Because typing is difficult with small keypads and small fonts, query suggestions allow the user to quickly enter items and reduce the number of characters that a user needs to type. At times, e.g., when the user is stressed for time, such query-inputting can also be problematic. This is particularly true when the user is engaged in search behavior on a computing device that is a small mobile device, where alpha-numeric textual input may be more difficult for some users.
For instance, a user may type “Br” in the input interface and the computing device may return query suggestions, such as “Bristol,” “Brooklyn,” “Bravo,” or “Broken.” The query suggestions are received from the conventional search engine. The conventional search engine receives the characters “Br” and identifies queries from its query log that partially match “Br.” In turn, the queries are transmitted to the user as query suggestions.
The conventional search engine generates suggestions that are agnostic of the location associated with the user. The suggestions received by the conventional computing device may be ranked based on query frequency. However, the suggestions are not ranked based on location. For instance, the conventional query suggestions may include entities from locations far from the current location of the user.